Intro
The purpose of this blog is to analyze what institutions believe to be the most impactful effects of war, and inspect those arguments using supporting data and visualizations from a variety of sources.
Content
You can include text, code, and output as usual.
Remember to take full advantage of Markdown and follow our Style
Guide.
Visualization 1
We selected a series of articles from different institutions (Banks,
Government, News & Media) that had titles relating to current
international conflicts and economic sentiment. This word frequency
analysis helped us decide where we should target our further analysis to
explore the impact that war has on the global macro environment. Among
this list: Oil, prices, and inflation were of great interest.
(sources listed below)
Jerome
Powell speaks on Raising the benchmark Fed Funds Rate
Visualization 2
CPI (Consumer Price Index) is the average price paid by a consumer for a “basket” of consumer goods. Here, we are looking at the CPI for a U.S. consumer from 2017-2022. CPI is also used as an indicator for inflation. The purpose of this plot is to provide some context for the further analysis that will be performed. The CPI has increased steadily over time, but we are interested in seeing if in recent years, global conflicts were drivers of that increase.
Further Exploration
Uses subsection syntax to get the tabs. Looks cool I think
Oil (Interactive Visuzlization)
You can make a bulleted list like this:
- item 1
- item 2
- item 3
Trade (Network)
You can make a numbered list like this
- First thing I want to say
- Second thing I want to say
- Third thing I want to say
Links
Examples and additional guidance are provided below.
Take note of the the default code chunk options in the
setup code chunk. For example, unlike the rest of the Rmd
files we worked in this semester, the default code chunk option is
echo = FALSE, so you will need to set
echo = TRUE for any code chunks you would like to display
in the blog. You should be thoughtful and intentional about the code you
choose to display.
You can include links using Markdown syntax as shown.
You should include links to relevant sites as you write. You should additionally include a list of references as the end of your blog with full citations (and relevant links).
Visualizations
Visualizations, particularly interactive ones, will be well-received. That said, do not overuse visualizations. You may be better off with one complicated but well-crafted visualization as opposed to many quick-and-dirty plots. Any plots should be well-thought-out, properly labeled, informative, and visually appealing.
If you want to include dynamic visualizations or tables, you should explore your options from packages that are built from htmlwidgets. These htmlwidgets-based packages offer ways to build lighterweight, dynamic visualizations or tables that don’t require an R server to run! A more complete list of packages is available on the linked website, but a short list includes:
- plotly: Interactive graphics with D3
- leaflet: Interactive maps with OpenStreetMap
- dygraphs: Interactive time series visualization
- visNetwork: Network graph visualization vis.js
- sparkline: Small inline charts
- threejs: Interactive 3D graphics
You may embed a published Shiny app in your blog if useful, but be aware that there is a limited window size for embedded objects, which tends to makes the user experience of the app worse relative to a dedicated Shiny app page. Additionally, Shiny apps will go idle after a few minutes and have to be reloaded by the user, which may also affect the user experience.
Any Shiny apps embedded in your blog should be accompanied by the link to the published Shiny app (I did this using a figure caption in the code chunk below, but you don’t have to incorporate the link in this way).
Tables
DT package
The DT package is great for making dynamic tables that can be displayed, searched, and filtered by the user without needing an R server or Shiny app!
Note: you should load any packages you use in the setup
code chunk as usual. The library() functions are shown
below just for demonstration.
library(DT)
mtcars %>%
select(mpg, cyl, hp) %>%
datatable(colnames = c("MPG", "Number of cylinders", "Horsepower"),
filter = 'top',
options = list(pageLength = 10, autoWidth = TRUE))
kableExtra package
You can also use kableExtra for customizing HTML tables.
library(kableExtra)
summary(cars) %>%
kbl(col.names = c("Speed", "Distance"),
row.names = FALSE) %>%
kable_styling(bootstrap_options = "striped",
full_width = FALSE) %>%
row_spec(0, bold = TRUE) %>%
column_spec(1:2, width = "1.5in")
| Speed | Distance |
|---|---|
| Min. : 4.0 | Min. : 2.00 |
| 1st Qu.:12.0 | 1st Qu.: 26.00 |
| Median :15.0 | Median : 36.00 |
| Mean :15.4 | Mean : 42.98 |
| 3rd Qu.:19.0 | 3rd Qu.: 56.00 |
| Max. :25.0 | Max. :120.00 |
Images
Images and gifs can be displayed using code chunks:
“Safe Space” by artist Kenesha Sneed
This is a figure caption
You may also use Markdown syntax for displaying images as shown below, but code chunks offer easier customization of the image size and alignment.